Advances in Dynamics and Fault Diagnosis of Bearing-Rotor Systems
A Special Issue of Machines (ISSN 2075-1702) belonging to the section "Machines Testing and Maintenance".
Deadline for manuscript submissions: 30 April 2027 | Viewed by 27
Editors
Interests: prognostics and health management; fault diagnosis; deep learning; industrial AI
Interests: nonlinear rotor dynamics; signal processing for rotating machinery; fault diagnosis; vibration control;
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Bearing–rotor systems are fundamental components of a wide range of rotating machinery, including turbines, generators, aero-engines, machine tools, electric motors, wind turbines, and transportation equipment. Their dynamic performance and operational condition have a direct influence on the safety, reliability, efficiency, and service life of modern mechanical systems. Accurate dynamic modeling and reliable fault diagnosis are therefore essential for understanding system behavior, detecting incipient defects, preventing unexpected failures, and supporting condition-based and predictive maintenance.
This Special Issue aims to bring together recent theoretical, numerical, experimental, and data-driven advances in the dynamics, condition monitoring, and fault diagnosis of bearing–rotor systems. It will provide a forum for researchers to present new findings concerning dynamic mechanisms, vibration characteristics, fault feature extraction, health assessment, and intelligent maintenance of rotating machinery. Particular emphasis will be placed on studies that establish meaningful connections between the physical dynamics of bearing–rotor systems and their measured condition-monitoring signals.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:
- Dynamic modeling and simulation of rolling-element bearings, motors, spindles, and other advanced bearing–rotor systems;
- Dynamic characteristics under variable-speed, variable-load, and transient operating conditions;
- Modeling and analysis of rotor imbalance, misalignment, cracks, looseness, structural defects, and other faults;
- Lubrication effects, wear, clearance, preload, friction, and thermal–mechanical coupling;
- Finite element, multibody dynamic, reduced-order, and digital twin models;
- Signal processing and feature extraction for weak, nonstationary, and compound faults;
- Machine learning and deep learning for fault detection, classification, and localization;
- Physics-informed, mechanism–data hybrid, and digital-twin-assisted diagnostic methods;
- Transfer learning, domain adaptation, domain generalization, and few-shot learning for fault diagnosis;
- Explainable and trustworthy AI for fault diagnosis;
- Fault severity assessment, degradation modeling, and remaining useful life prediction;
- Uncertainty quantification, robustness, and reliability evaluation of diagnostic and prognostic methods;
- Industrial applications and case studies involving bearing–rotor systems.
I/We look forward to receiving your contributions.
Dr. Pengcheng Xia
Dr. Xinxing Ma
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- bearing-rotor systems
- rotor dynamics
- fault diagnosis
- signal processing
- predictive maintenance
- artificial intelligence
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
